Prior art customer care and tech support tools are inefficient for subscribers and costly for operators. When customers encounter a problem with their mobile device they have to endure lengthy phone calls, navigating decision trees, and website or forum searches that deliver static un-personalized content with little hope for finding an accurate resolution to their problem. Consumers today are busier and less patient than ever—they need quick, accurate, and personalized answers to their questions and do not want to navigate through menus and FAQs to find answers to their questions anymore.
Although prior art self-care systems enable customers to check their balances, view financial transactions and invoices, modify personal details, change billing cycle dates, modify payment methods, change service parameters, and most importantly troubleshoot some of the basic issues that they may encounter; they still have room for improvement.
As markets become saturated companies are in a fierce battle with their rivals to create levels of differentiation beyond price. Thus improved customer care that focuses on call volume reduction or call avoidance helps towards lowering the cost of customer support. Additionally fast resolution to customer problems/complaints results in more satisfied customers that increases customer retention.
Mean Time-to-Resolution (MTTR) helps organizations track the average amount of time spent resolving customer issues. Mean Time to Resolve (MTTR) is a service level metric that measures the average elapsed time from when an incident is reported until the incident is resolved. MTTR is typically measured in hours or days depending on the nature of the product or system being supported.
Typically Mean Time-to-Resolution (MTTR) tends to be in the domain of technical support, where organizations and their customers share the common goal of resolving customer issues as quickly as possible. For customers, this means returning to “operational status” as quickly as possible; for service providers this means keeping support costs low while maintaining a high level of customer satisfaction.
Many factors can contribute to MTTR. These factors include the communication skills and technical expertise of the representative and the customer, the representative's access to relevant resources, and their troubleshooting skills. It is well known that the majority of time is taken in identifying the root cause of the problem and the minority in actually fixing it. Thus quickly identifying where in the delivery chain or which components are causing or being affected by the problem can lead to a significant reduction in the problem identification phase and hence MTTR.
In general problems that are left to escalate tend to have a much higher cost to the organisation. Reducing the MTTR is a key objective of many operations groups with the desirable outcome of improved stakeholder satisfaction.
The current method of gathering and obtaining device information required for diagnostics is manual and therefore complex, time-consuming and prone to human errors. In the course of a customer care session for a device, a CSR (Customer Service Representative) must undertake the extensive and time-consuming task of asking the user complex questions pertaining to their wireless devices for problem diagnosis. This requires CSRs to be experts on many types of devices and their applications, and also requires users to spend increased time on the telephone to receive support for their applications. The result is increased support costs, increased call handling times, complex diagnostic processes and overall frustration.
Such prior methods lack automation and the user (or the CSR) is required to sift through massive amounts of data manually to get to the relevant information.